Instructions to use ryuotter/t2a_exp3_mwoz_sft with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use ryuotter/t2a_exp3_mwoz_sft with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("meta-llama/Llama-3.1-8B-Instruct") model = PeftModel.from_pretrained(base_model, "ryuotter/t2a_exp3_mwoz_sft") - Notebooks
- Google Colab
- Kaggle
LoRA Adapter for Llama-3.1-8B-Instruct
SFT-trained LoRA adapter for MultiWOZ task-oriented dialogue.
Usage
from transformers import AutoModelForCausalLM, AutoTokenizer
from peft import PeftModel
base_model = AutoModelForCausalLM.from_pretrained("meta-llama/Llama-3.1-8B-Instruct")
tokenizer = AutoTokenizer.from_pretrained("meta-llama/Llama-3.1-8B-Instruct")
model = PeftModel.from_pretrained(base_model, "niklasfalk/thesis-sft-mwoz-adapter-llama31-8b-20250910-203131")
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Model tree for ryuotter/t2a_exp3_mwoz_sft
Base model
meta-llama/Llama-3.1-8B Finetuned
meta-llama/Llama-3.1-8B-Instruct